update

example.py

@@ -0,0 +1,18 @@
+import numpy as np
+from kdtree import KDTree
+from sklearn import datasets
+
+def test(data):
+    num_samples, _ = data.shape
+
+    ratio = 0.85
+    X_train = data[:int(ratio*num_samples), :]
+    X_test = data[int(ratio*num_samples):, :]
+
+    kd_tree = KDTree(X_train)
+    kd_tree.build_tree()
+
+    nn = kd_tree.query(X_test, 4)
+
+if __name__ == "__main__":
+    test(datasets)

setup.py

@@ -0,0 +1,24 @@
+import os
+import sys
+from setuptools import setup
+
+setup(name ="kdtree",
+    version = "1.0.0",
+    description = "Python library for optimization descent algorithms",
+    long_description = open("README.md").read(),
+    url = "https://github.com/qzhao19/kdtree",
+    author = 'Qi ZHAO',
+    author_email = '[email protected]',
+    license = "MIT",
+    packages = ['kdtree'],
+    install_requires = ["numpy>=1.19.5"],
+    classifiers=[
+        "Intended Audience :: Science/Research",
+        "Topic :: Scientific/Engineering :: Mathematics :: Machine Learning Algorithms",
+        "License :: OSI Approved :: MIT License",
+        "Programming Language :: Python :: 3",
+        "Programming Language :: Python :: 3.6",
+        'Operating System :: Unix',
+    ],
+    keywords='kdtree',
+)